Profiling Report

Dataset statistics

Number of variables	46
Number of observations	131
Missing cells	217
Missing cells (%)	3.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	47.2 KiB
Average record size in memory	369.0 B

Variable types

DateTime	5
Numeric	11
Categorical	29
Unsupported	1

Warnings

`num_ide_` has a high cardinality: 131 distinct values	High cardinality
`no_ide_rn` has a high cardinality: 131 distinct values	High cardinality
`semana` is highly correlated with `nreg`	High correlation
`nacionali_` is highly correlated with `gp_migrant`	High correlation
`cod_dpto_o` is highly correlated with `cod_dpto_r`	High correlation
`cod_mun_o` is highly correlated with `cod_mun_r`	High correlation
`gp_migrant` is highly correlated with `nacionali_`	High correlation
`gp_gestan` is highly correlated with `gp_otros`	High correlation
`sem_ges_` is highly correlated with `edad_rn` and 1 other fields	High correlation
`gp_otros` is highly correlated with `gp_gestan`	High correlation
`cod_dpto_r` is highly correlated with `cod_dpto_o`	High correlation
`cod_mun_r` is highly correlated with `cod_mun_o`	High correlation
`edad_rn` is highly correlated with `sem_ges_`	High correlation
`sem_gest` is highly correlated with `sem_ges_`	High correlation
`num_em_pre` is highly correlated with `num_hi_viv`	High correlation
`num_hi_viv` is highly correlated with `num_em_pre`	High correlation
`nreg` is highly correlated with `semana`	High correlation
`semana` is highly correlated with `nreg`	High correlation
`cod_pre` is highly correlated with `nit_upgd`	High correlation
`nacionali_` is highly correlated with `gp_migrant`	High correlation
`cod_dpto_o` is highly correlated with `cod_dpto_r`	High correlation
`cod_mun_o` is highly correlated with `cod_mun_r`	High correlation
`ocupacion_` is highly correlated with `nit_upgd`	High correlation
`gp_migrant` is highly correlated with `nacionali_`	High correlation
`gp_gestan` is highly correlated with `gp_otros`	High correlation
`sem_ges_` is highly correlated with `sem_gest`	High correlation
`gp_otros` is highly correlated with `gp_gestan`	High correlation
`cod_dpto_r` is highly correlated with `cod_dpto_o`	High correlation
`cod_mun_r` is highly correlated with `cod_mun_o`	High correlation
`nit_upgd` is highly correlated with `cod_pre` and 1 other fields	High correlation
`sem_gest` is highly correlated with `sem_ges_`	High correlation
`num_em_pre` is highly correlated with `num_hi_viv`	High correlation
`num_hi_viv` is highly correlated with `num_em_pre`	High correlation
`nreg` is highly correlated with `semana`	High correlation
`semana` is highly correlated with `nreg`	High correlation
`nacionali_` is highly correlated with `gp_migrant`	High correlation
`cod_dpto_o` is highly correlated with `cod_dpto_r`	High correlation
`cod_mun_o` is highly correlated with `cod_mun_r`	High correlation
`gp_migrant` is highly correlated with `nacionali_`	High correlation
`gp_gestan` is highly correlated with `gp_otros`	High correlation
`sem_ges_` is highly correlated with `sem_gest`	High correlation
`gp_otros` is highly correlated with `gp_gestan`	High correlation
`cod_dpto_r` is highly correlated with `cod_dpto_o`	High correlation
`cod_mun_r` is highly correlated with `cod_mun_o`	High correlation
`sem_gest` is highly correlated with `sem_ges_`	High correlation
`num_em_pre` is highly correlated with `num_hi_viv`	High correlation
`num_hi_viv` is highly correlated with `num_em_pre`	High correlation
`nreg` is highly correlated with `semana`	High correlation
`cod_ase_` is highly correlated with `nit_upgd` and 11 other fields	High correlation
`ndep_proce` is highly correlated with `cod_mun_r` and 9 other fields	High correlation
`gp_migrant` is highly correlated with `nacionali_` and 8 other fields	High correlation
`cod_mun_r` is highly correlated with `ndep_proce` and 9 other fields	High correlation
`nacionali_` is highly correlated with `gp_migrant` and 8 other fields	High correlation
`niv_edu_ma` is highly correlated with `nit_upgd` and 3 other fields	High correlation
`edad_` is highly correlated with `num_hi_viv` and 4 other fields	High correlation
`cod_dpto_r` is highly correlated with `ndep_proce` and 8 other fields	High correlation
`nit_upgd` is highly correlated with `cod_ase_` and 15 other fields	High correlation
`ndep_resi` is highly correlated with `ndep_proce` and 8 other fields	High correlation
`pac_hos_` is highly correlated with `cod_ase_` and 2 other fields	High correlation
`gp_gestan` is highly correlated with `cod_ase_` and 7 other fields	High correlation
`version` is highly correlated with `tip_doc_rn` and 7 other fields	High correlation
`cod_mun_o` is highly correlated with `ndep_proce` and 11 other fields	High correlation
`tip_doc_rn` is highly correlated with `cod_ase_` and 7 other fields	High correlation
`tip_ss_` is highly correlated with `cod_ase_` and 8 other fields	High correlation
`num_em_pre` is highly correlated with `fec_aju_` and 2 other fields	High correlation
`fec_aju_` is highly correlated with `ndep_proce` and 29 other fields	High correlation
`area_` is highly correlated with `cod_mun_r` and 6 other fields	High correlation
`sem_ges_` is highly correlated with `cod_ase_` and 11 other fields	High correlation
`talla_nace` is highly correlated with `cod_mun_o` and 8 other fields	High correlation
`num_hi_viv` is highly correlated with `edad_` and 5 other fields	High correlation
`sem_gest` is highly correlated with `gp_migrant` and 7 other fields	High correlation
`gp_otros` is highly correlated with `cod_ase_` and 7 other fields	High correlation
`nmun_proce` is highly correlated with `cod_ase_` and 13 other fields	High correlation
`peso_nacer` is highly correlated with `nmun_proce` and 1 other fields	High correlation
`nmun_resi` is highly correlated with `cod_ase_` and 12 other fields	High correlation
`mult_embar` is highly correlated with `fec_aju_` and 2 other fields	High correlation
`semana` is highly correlated with `version` and 5 other fields	High correlation
`nom_upgd` is highly correlated with `cod_ase_` and 10 other fields	High correlation
`fec_not` is highly correlated with `cod_ase_` and 28 other fields	High correlation
`fecha_nac` is highly correlated with `ndep_proce` and 29 other fields	High correlation
`nombre_nacionalidad` is highly correlated with `gp_migrant` and 8 other fields	High correlation
`tip_ide_` is highly correlated with `gp_migrant` and 6 other fields	High correlation
`ocupacion_` is highly correlated with `fec_not` and 2 other fields	High correlation
`cod_dpto_o` is highly correlated with `ndep_proce` and 9 other fields	High correlation
`estrato_` is highly correlated with `gp_migrant` and 10 other fields	High correlation
`edad_rn` is highly correlated with `version` and 5 other fields	High correlation
`fec_con_` is highly correlated with `edad_` and 21 other fields	High correlation
`sexo` is highly correlated with `fecha_nac` and 1 other fields	High correlation
`nreg` is highly correlated with `version` and 5 other fields	High correlation
`cod_pre` is highly correlated with `cod_ase_` and 3 other fields	High correlation
`cod_ase_` is highly correlated with `gp_migrant` and 7 other fields	High correlation
`ndep_proce` is highly correlated with `cod_dpto_r` and 5 other fields	High correlation
`gp_migrant` is highly correlated with `cod_ase_` and 5 other fields	High correlation
`nacionali_` is highly correlated with `cod_ase_` and 5 other fields	High correlation
`cod_dpto_r` is highly correlated with `ndep_proce` and 5 other fields	High correlation
`nit_upgd` is highly correlated with `cod_ase_` and 4 other fields	High correlation
`ndep_resi` is highly correlated with `ndep_proce` and 5 other fields	High correlation
`pac_hos_` is highly correlated with `sem_ges_`	High correlation
`gp_gestan` is highly correlated with `nit_upgd` and 3 other fields	High correlation
`tip_doc_rn` is highly correlated with `cod_ase_` and 3 other fields	High correlation
`tip_ss_` is highly correlated with `cod_ase_` and 4 other fields	High correlation
`area_` is highly correlated with `nmun_proce` and 1 other fields	High correlation
`sem_ges_` is highly correlated with `ndep_proce` and 7 other fields	High correlation
`sem_gest` is highly correlated with `sem_ges_`	High correlation
`gp_otros` is highly correlated with `cod_ase_` and 4 other fields	High correlation
`nmun_proce` is highly correlated with `ndep_proce` and 5 other fields	High correlation
`nmun_resi` is highly correlated with `ndep_proce` and 5 other fields	High correlation
`nom_upgd` is highly correlated with `cod_ase_` and 7 other fields	High correlation
`tip_ide_` is highly correlated with `gp_migrant` and 3 other fields	High correlation
`nombre_nacionalidad` is highly correlated with `cod_ase_` and 5 other fields	High correlation
`cod_dpto_o` is highly correlated with `ndep_proce` and 5 other fields	High correlation
`estrato_` is highly correlated with `tip_doc_rn`	High correlation
`cod_ase_` has 23 (17.6%) missing values	Missing
`estrato_` has 67 (51.1%) missing values	Missing
`sem_ges_` has 107 (81.7%) missing values	Missing
`nit_upgd` has 9 (6.9%) missing values	Missing
`niv_edu_ma` has 2 (1.5%) missing values	Missing
`nom_upgd` has 9 (6.9%) missing values	Missing
`num_ide_` is uniformly distributed	Uniform
`no_ide_rn` is uniformly distributed	Uniform
`nreg` is uniformly distributed	Uniform
`num_ide_` has unique values	Unique
`no_ide_rn` has unique values	Unique
`nreg` has unique values	Unique
`fec_hos_` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`edad_rn` has 5 (3.8%) zeros	Zeros
`num_em_pre` has 62 (47.3%) zeros	Zeros

Reproduction

Analysis started	2021-07-10 22:40:54.191591
Analysis finished	2021-07-10 22:46:40.725209
Duration	5 minutes and 46.53 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

fec_not
Date

HIGH CORRELATION

Distinct	79
Distinct (%)	60.3%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

Minimum	2021-01-06 00:00:00
Maximum	2021-06-21 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

semana
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	23
Distinct (%)	17.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.16030534

Minimum	1
Maximum	23
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	11
Q3	16
95-th percentile	21.5
Maximum	23
Range	22
Interquartile range (IQR)	11

Descriptive statistics

Standard deviation	6.141682047
Coefficient of variation (CV)	0.5503148756
Kurtosis	-1.052039502
Mean	11.16030534
Median Absolute Deviation (MAD)	5
Skewness	0.07958469032
Sum	1462
Variance	37.72025837
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
5	10	7.6%
8	9	6.9%
10	9	6.9%
12	8	6.1%
14	8	6.1%
4	8	6.1%
17	8	6.1%
11	8	6.1%
16	7	5.3%
2	7	5.3%
Other values (13)	49	37.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	5	3.8%
2	7	5.3%
3	4	3.1%
4	8	6.1%
5	10	7.6%
6	2	1.5%
7	4	3.1%
8	9	6.9%
9	3	2.3%
10	9	6.9%

Value	Count	Frequency (%)
23	1	0.8%
22	6	4.6%
21	4	3.1%
20	3	2.3%
19	4	3.1%
18	4	3.1%
17	8	6.1%
16	7	5.3%
15	6	4.6%
14	8	6.1%

cod_pre
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	5.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6801990104

Minimum	6800100431
Maximum	6827601666
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	6800100431
5-th percentile	6800100431
Q1	6800100431
median	6800100792
Q3	6800101157
95-th percentile	6827601192
Maximum	6827601666
Range	27501235
Interquartile range (IQR)	726

Descriptive statistics

Standard deviation	6982918.869
Coefficient of variation (CV)	0.001026599387
Kurtosis	10.05445947
Mean	6801990104
Median Absolute Deviation (MAD)	361
Skewness	3.449807693
Sum	8.910607036 × 10¹¹
Variance	4.876115593 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
6800100792	43	32.8%
6800100431	40	30.5%
6800101157	27	20.6%
6800100701	12	9.2%
6827601666	7	5.3%
6827600717	1	0.8%
6827600289	1	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6800100431	40	30.5%
6800100701	12	9.2%
6800100792	43	32.8%
6800101157	27	20.6%
6827600289	1	0.8%
6827600717	1	0.8%
6827601666	7	5.3%

Value	Count	Frequency (%)
6827601666	7	5.3%
6827600717	1	0.8%
6827600289	1	0.8%
6800101157	27	20.6%
6800100792	43	32.8%
6800100701	12	9.2%
6800100431	40	30.5%

tip_ide_
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	4.6%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

CC	96
CE	14
TI	12
MS	6
AS	2

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	262
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.8%

Sample

1st row	CC
2nd row	CC
3rd row	CC
4th row	CC
5th row	CC

Common Values

Value	Count	Frequency (%)
CC	96	73.3%
CE	14	10.7%
TI	12	9.2%
MS	6	4.6%
AS	2	1.5%
PE	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
cc	96	73.3%
ce	14	10.7%
ti	12	9.2%
ms	6	4.6%
as	2	1.5%
pe	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
C	206	78.6%
E	15	5.7%
T	12	4.6%
I	12	4.6%
S	8	3.1%
M	6	2.3%
A	2	0.8%
P	1	0.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	262	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
C	206	78.6%
E	15	5.7%
T	12	4.6%
I	12	4.6%
S	8	3.1%
M	6	2.3%
A	2	0.8%
P	1	0.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	262	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
C	206	78.6%
E	15	5.7%
T	12	4.6%
I	12	4.6%
S	8	3.1%
M	6	2.3%
A	2	0.8%
P	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	262	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
C	206	78.6%
E	15	5.7%
T	12	4.6%
I	12	4.6%
S	8	3.1%
M	6	2.3%
A	2	0.8%
P	1	0.4%

num_ide_
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	131
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1007665960	1
1005484877	1
VEN27626337	1
1095929685	1
1101048096	1
Other values (126)	126

Length

Max length	18
Median length	10
Mean length	10.09160305
Min length	8

Characters and Unicode

Total characters	1322
Distinct characters	14
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	131 ?
Unique (%)	100.0%

Sample

1st row	37372773
2nd row	1098713904
3rd row	1099940520
4th row	1000251004
5th row	1000251004-1

Common Values

Value	Count	Frequency (%)
1007665960	1	0.8%
1005484877	1	0.8%
VEN27626337	1	0.8%
1095929685	1	0.8%
1101048096	1	0.8%
1005104784	1	0.8%
1098710937	1	0.8%
37864414	1	0.8%
1005136505	1	0.8%
1193149502	1	0.8%
Other values (121)	121	92.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1007665960	1	0.8%
1098749294	1	0.8%
1005104784	1	0.8%
1098710937	1	0.8%
37864414	1	0.8%
1005136505	1	0.8%
ven721454102091991	1	0.8%
1193149502	1	0.8%
1065902103	1	0.8%
1098631893	1	0.8%
Other values (121)	121	92.4%

Most occurring characters

Value	Count	Frequency (%)
0	213	16.1%
1	210	15.9%
9	139	10.5%
8	125	9.5%
2	98	7.4%
5	97	7.3%
3	96	7.3%
7	96	7.3%
6	89	6.7%
4	84	6.4%
Other values (4)	75	5.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1247	94.3%
Uppercase Letter	69	5.2%
Dash Punctuation	6	0.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	213	17.1%
1	210	16.8%
9	139	11.1%
8	125	10.0%
2	98	7.9%
5	97	7.8%
3	96	7.7%
7	96	7.7%
6	89	7.1%
4	84	6.7%

Uppercase Letter

Value	Count	Frequency (%)
V	23	33.3%
E	23	33.3%
N	23	33.3%

Dash Punctuation

Value	Count	Frequency (%)
-	6	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1253	94.8%
Latin	69	5.2%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	213	17.0%
1	210	16.8%
9	139	11.1%
8	125	10.0%
2	98	7.8%
5	97	7.7%
3	96	7.7%
7	96	7.7%
6	89	7.1%
4	84	6.7%

Latin

Value	Count	Frequency (%)
V	23	33.3%
E	23	33.3%
N	23	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1322	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	213	16.1%
1	210	15.9%
9	139	10.5%
8	125	9.5%
2	98	7.4%
5	97	7.3%
3	96	7.3%
7	96	7.3%
6	89	6.7%
4	84	6.4%
Other values (4)	75	5.7%

edad_
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	29
Distinct (%)	22.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25.76335878

Minimum	15
Maximum	47
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	15
5-th percentile	16
Q1	20
median	24
Q3	30
95-th percentile	38.5
Maximum	47
Range	32
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	7.362934262
Coefficient of variation (CV)	0.2857909299
Kurtosis	-0.185736991
Mean	25.76335878
Median Absolute Deviation (MAD)	5
Skewness	0.6570749812
Sum	3375
Variance	54.21280094
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
20	15	11.5%
29	10	7.6%
24	10	7.6%
23	9	6.9%
17	9	6.9%
25	7	5.3%
34	5	3.8%
26	5	3.8%
15	5	3.8%
21	5	3.8%
Other values (19)	51	38.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
15	5	3.8%
16	4	3.1%
17	9	6.9%
18	4	3.1%
19	3	2.3%
20	15	11.5%
21	5	3.8%
22	4	3.1%
23	9	6.9%
24	10	7.6%

Value	Count	Frequency (%)
47	1	0.8%
45	2	1.5%
42	1	0.8%
40	1	0.8%
39	2	1.5%
38	2	1.5%
37	4	3.1%
36	4	3.1%
35	2	1.5%
34	5	3.8%

nacionali_
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

170	108
862	23

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	393
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	170
2nd row	170
3rd row	170
4th row	170
5th row	170

Common Values

Value	Count	Frequency (%)
170	108	82.4%
862	23	17.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
170	108	82.4%
862	23	17.6%

Most occurring characters

Value	Count	Frequency (%)
1	108	27.5%
7	108	27.5%
0	108	27.5%
8	23	5.9%
6	23	5.9%
2	23	5.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	393	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	108	27.5%
7	108	27.5%
0	108	27.5%
8	23	5.9%
6	23	5.9%
2	23	5.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	393	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	108	27.5%
7	108	27.5%
0	108	27.5%
8	23	5.9%
6	23	5.9%
2	23	5.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	393	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	108	27.5%
7	108	27.5%
0	108	27.5%
8	23	5.9%
6	23	5.9%
2	23	5.9%

nombre_nacionalidad
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

COLOMBIA	108
VENEZUELA	23

Length

Max length	9
Median length	8
Mean length	8.175572519
Min length	8

Characters and Unicode

Total characters	1071
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	COLOMBIA
2nd row	COLOMBIA
3rd row	COLOMBIA
4th row	COLOMBIA
5th row	COLOMBIA

Common Values

Value	Count	Frequency (%)
COLOMBIA	108	82.4%
VENEZUELA	23	17.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
colombia	108	82.4%
venezuela	23	17.6%

Most occurring characters

Value	Count	Frequency (%)
O	216	20.2%
L	131	12.2%
A	131	12.2%
C	108	10.1%
M	108	10.1%
B	108	10.1%
I	108	10.1%
E	69	6.4%
V	23	2.1%
N	23	2.1%
Other values (2)	46	4.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1071	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
O	216	20.2%
L	131	12.2%
A	131	12.2%
C	108	10.1%
M	108	10.1%
B	108	10.1%
I	108	10.1%
E	69	6.4%
V	23	2.1%
N	23	2.1%
Other values (2)	46	4.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1071	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
O	216	20.2%
L	131	12.2%
A	131	12.2%
C	108	10.1%
M	108	10.1%
B	108	10.1%
I	108	10.1%
E	69	6.4%
V	23	2.1%
N	23	2.1%
Other values (2)	46	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1071	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
O	216	20.2%
L	131	12.2%
A	131	12.2%
C	108	10.1%
M	108	10.1%
B	108	10.1%
I	108	10.1%
E	69	6.4%
V	23	2.1%
N	23	2.1%
Other values (2)	46	4.3%

cod_dpto_o
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

68	125
20	3
13	2
54	1

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	262
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.8%

Sample

1st row	68
2nd row	68
3rd row	68
4th row	68
5th row	68

Common Values

Value	Count	Frequency (%)
68	125	95.4%
20	3	2.3%
13	2	1.5%
54	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
68	125	95.4%
20	3	2.3%
13	2	1.5%
54	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
6	125	47.7%
8	125	47.7%
2	3	1.1%
0	3	1.1%
1	2	0.8%
3	2	0.8%
5	1	0.4%
4	1	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	262	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
6	125	47.7%
8	125	47.7%
2	3	1.1%
0	3	1.1%
1	2	0.8%
3	2	0.8%
5	1	0.4%
4	1	0.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	262	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
6	125	47.7%
8	125	47.7%
2	3	1.1%
0	3	1.1%
1	2	0.8%
3	2	0.8%
5	1	0.4%
4	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	262	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
6	125	47.7%
8	125	47.7%
2	3	1.1%
0	3	1.1%
1	2	0.8%
3	2	0.8%
5	1	0.4%
4	1	0.4%

cod_mun_o
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	21
Distinct (%)	16.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	224.2366412

Minimum	1
Maximum	855
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	128
Q3	368
95-th percentile	679.5
Maximum	855
Range	854
Interquartile range (IQR)	367

Descriptive statistics

Standard deviation	256.5955462
Coefficient of variation (CV)	1.144306947
Kurtosis	-0.662124686
Mean	224.2366412
Median Absolute Deviation (MAD)	127
Skewness	0.7642781076
Sum	29375
Variance	65841.27434
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
1	60	45.8%
276	22	16.8%
547	15	11.5%
307	7	5.3%
820	4	3.1%
11	3	2.3%
615	3	2.3%
572	2	1.5%
689	2	1.5%
670	2	1.5%
Other values (11)	11	8.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	60	45.8%
11	3	2.3%
20	1	0.8%
79	1	0.8%
128	1	0.8%
190	1	0.8%
276	22	16.8%
298	1	0.8%
307	7	5.3%
318	1	0.8%

Value	Count	Frequency (%)
855	1	0.8%
820	4	3.1%
689	2	1.5%
670	2	1.5%
655	1	0.8%
615	3	2.3%
572	2	1.5%
547	15	11.5%
464	1	0.8%
444	1	0.8%

area_
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	110
3	19
2	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	2
3rd row	3
4th row	3
5th row	3

Common Values

Value	Count	Frequency (%)
1	110	84.0%
3	19	14.5%
2	2	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	110	84.0%
3	19	14.5%
2	2	1.5%

Most occurring characters

Value	Count	Frequency (%)
1	110	84.0%
3	19	14.5%
2	2	1.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	110	84.0%
3	19	14.5%
2	2	1.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	110	84.0%
3	19	14.5%
2	2	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	110	84.0%
3	19	14.5%
2	2	1.5%

ocupacion_
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	5.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9899.198473

Minimum	3221
Maximum	9999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	3221
5-th percentile	9996
Q1	9996
median	9997
Q3	9999
95-th percentile	9999
Maximum	9999
Range	6778
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	764.2550865
Coefficient of variation (CV)	0.07720373408
Kurtosis	65.19398544
Mean	9899.198473
Median Absolute Deviation (MAD)	2
Skewness	-8.090420734
Sum	1296795
Variance	584085.8372
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
9999	63	48.1%
9996	57	43.5%
9997	5	3.8%
9950	3	2.3%
4419	1	0.8%
9611	1	0.8%
3221	1	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3221	1	0.8%
4419	1	0.8%
9611	1	0.8%
9950	3	2.3%
9996	57	43.5%
9997	5	3.8%
9999	63	48.1%

Value	Count	Frequency (%)
9999	63	48.1%
9997	5	3.8%
9996	57	43.5%
9950	3	2.3%
9611	1	0.8%
4419	1	0.8%
3221	1	0.8%

tip_ss_
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

C	59
S	47
N	23
P	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	S
2nd row	S
3rd row	S
4th row	S
5th row	S

Common Values

Value	Count	Frequency (%)
C	59	45.0%
S	47	35.9%
N	23	17.6%
P	2	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
c	59	45.0%
s	47	35.9%
n	23	17.6%
p	2	1.5%

Most occurring characters

Value	Count	Frequency (%)
C	59	45.0%
S	47	35.9%
N	23	17.6%
P	2	1.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	131	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
C	59	45.0%
S	47	35.9%
N	23	17.6%
P	2	1.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	131	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
C	59	45.0%
S	47	35.9%
N	23	17.6%
P	2	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
C	59	45.0%
S	47	35.9%
N	23	17.6%
P	2	1.5%

cod_ase_
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	22
Distinct (%)	20.4%
Missing	23
Missing (%)	17.6%
Memory size	1.1 KiB

EPS005	15
EPS002	14
EPSS41	12
ESS133	10
ESS024	7
Other values (17)	50

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	648
Distinct characters	15
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	9 ?
Unique (%)	8.3%

Sample

1st row	EPSS41
2nd row	EPSS41
3rd row	ESS133
4th row	ESS024
5th row	ESS024

Common Values

Value	Count	Frequency (%)
EPS005	15	11.5%
EPS002	14	10.7%
EPSS41	12	9.2%
ESS133	10	7.6%
ESS024	7	5.3%
ESS062	7	5.3%
EPS017	7	5.3%
EPS037	6	4.6%
EPS010	6	4.6%
EPSS37	6	4.6%
Other values (12)	18	13.7%
(Missing)	23	17.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
eps005	15	13.9%
eps002	14	13.0%
epss41	12	11.1%
ess133	10	9.3%
eps017	7	6.5%
ess024	7	6.5%
ess062	7	6.5%
eps037	6	5.6%
epss37	6	5.6%
eps010	6	5.6%
Other values (12)	18	16.7%

Most occurring characters

Value	Count	Frequency (%)
S	158	24.4%
0	111	17.1%
E	108	16.7%
P	78	12.0%
1	42	6.5%
3	39	6.0%
2	31	4.8%
4	22	3.4%
7	20	3.1%
5	16	2.5%
Other values (5)	23	3.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	351	54.2%
Decimal Number	297	45.8%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	111	37.4%
1	42	14.1%
3	39	13.1%
2	31	10.4%
4	22	7.4%
7	20	6.7%
5	16	5.4%
6	15	5.1%
9	1	0.3%

Uppercase Letter

Value	Count	Frequency (%)
S	158	45.0%
E	108	30.8%
P	78	22.2%
C	4	1.1%
R	2	0.6%
M	1	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	351	54.2%
Common	297	45.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	111	37.4%
1	42	14.1%
3	39	13.1%
2	31	10.4%
4	22	7.4%
7	20	6.7%
5	16	5.4%
6	15	5.1%
9	1	0.3%

Latin

Value	Count	Frequency (%)
S	158	45.0%
E	108	30.8%
P	78	22.2%
C	4	1.1%
R	2	0.6%
M	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	648	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
S	158	24.4%
0	111	17.1%
E	108	16.7%
P	78	12.0%
1	42	6.5%
3	39	6.0%
2	31	4.8%
4	22	3.4%
7	20	3.1%
5	16	2.5%
Other values (5)	23	3.5%

estrato_
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	6.2%
Missing	67
Missing (%)	51.1%
Memory size	1.1 KiB

2.0	28
3.0	22
1.0	13
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	192
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.6%

Sample

1st row	1.0
2nd row	1.0
3rd row	2.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	28	21.4%
3.0	22	16.8%
1.0	13	9.9%
4.0	1	0.8%
(Missing)	67	51.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	28	43.8%
3.0	22	34.4%
1.0	13	20.3%
4.0	1	1.6%

Most occurring characters

Value	Count	Frequency (%)
.	64	33.3%
0	64	33.3%
2	28	14.6%
3	22	11.5%
1	13	6.8%
4	1	0.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	128	66.7%
Other Punctuation	64	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	64	50.0%
2	28	21.9%
3	22	17.2%
1	13	10.2%
4	1	0.8%

Other Punctuation

Value	Count	Frequency (%)
.	64	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	192	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	64	33.3%
0	64	33.3%
2	28	14.6%
3	22	11.5%
1	13	6.8%
4	1	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	192	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	64	33.3%
0	64	33.3%
2	28	14.6%
3	22	11.5%
1	13	6.8%
4	1	0.5%

gp_migrant
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

2	108
1	23

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	108	82.4%
1	23	17.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	108	82.4%
1	23	17.6%

Most occurring characters

Value	Count	Frequency (%)
2	108	82.4%
1	23	17.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	108	82.4%
1	23	17.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	108	82.4%
1	23	17.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	108	82.4%
1	23	17.6%

gp_gestan
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

2	107
1	24

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	107	81.7%
1	24	18.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	107	81.7%
1	24	18.3%

Most occurring characters

Value	Count	Frequency (%)
2	107	81.7%
1	24	18.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	107	81.7%
1	24	18.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	107	81.7%
1	24	18.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	107	81.7%
1	24	18.3%

sem_ges_
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	16.7%
Missing	107
Missing (%)	81.7%
Memory size	1.1 KiB

37.0	17
38.0	3
39.0	3
32.0	1

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	96
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	4.2%

Sample

1st row	38.0
2nd row	37.0
3rd row	38.0
4th row	37.0
5th row	39.0

Common Values

Value	Count	Frequency (%)
37.0	17	13.0%
38.0	3	2.3%
39.0	3	2.3%
32.0	1	0.8%
(Missing)	107	81.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
37.0	17	70.8%
38.0	3	12.5%
39.0	3	12.5%
32.0	1	4.2%

Most occurring characters

Value	Count	Frequency (%)
3	24	25.0%
.	24	25.0%
0	24	25.0%
7	17	17.7%
8	3	3.1%
9	3	3.1%
2	1	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	72	75.0%
Other Punctuation	24	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	24	33.3%
0	24	33.3%
7	17	23.6%
8	3	4.2%
9	3	4.2%
2	1	1.4%

Other Punctuation

Value	Count	Frequency (%)
.	24	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	96	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	24	25.0%
.	24	25.0%
0	24	25.0%
7	17	17.7%
8	3	3.1%
9	3	3.1%
2	1	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	96	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	24	25.0%
.	24	25.0%
0	24	25.0%
7	17	17.7%
8	3	3.1%
9	3	3.1%
2	1	1.0%

gp_otros
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	112
2	19

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	112	85.5%
2	19	14.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	112	85.5%
2	19	14.5%

Most occurring characters

Value	Count	Frequency (%)
1	112	85.5%
2	19	14.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	112	85.5%
2	19	14.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	112	85.5%
2	19	14.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	112	85.5%
2	19	14.5%

cod_dpto_r
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

68	126
20	3
54	1
13	1

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	262
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.5%

Sample

1st row	68
2nd row	68
3rd row	68
4th row	68
5th row	68

Common Values

Value	Count	Frequency (%)
68	126	96.2%
20	3	2.3%
54	1	0.8%
13	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
68	126	96.2%
20	3	2.3%
54	1	0.8%
13	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
6	126	48.1%
8	126	48.1%
2	3	1.1%
0	3	1.1%
1	1	0.4%
3	1	0.4%
5	1	0.4%
4	1	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	262	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
6	126	48.1%
8	126	48.1%
2	3	1.1%
0	3	1.1%
1	1	0.4%
3	1	0.4%
5	1	0.4%
4	1	0.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	262	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
6	126	48.1%
8	126	48.1%
2	3	1.1%
0	3	1.1%
1	1	0.4%
3	1	0.4%
5	1	0.4%
4	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	262	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
6	126	48.1%
8	126	48.1%
2	3	1.1%
0	3	1.1%
1	1	0.4%
3	1	0.4%
5	1	0.4%
4	1	0.4%

cod_mun_r
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	20
Distinct (%)	15.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	200.9847328

Minimum	1
Maximum	855
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	307
95-th percentile	635
Maximum	855
Range	854
Interquartile range (IQR)	306

Descriptive statistics

Standard deviation	246.0838501
Coefficient of variation (CV)	1.224390762
Kurtosis	-0.5551265459
Mean	200.9847328
Median Absolute Deviation (MAD)	0
Skewness	0.8519519219
Sum	26329
Variance	60557.2613
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
1	66	50.4%
276	20	15.3%
547	15	11.5%
307	7	5.3%
11	3	2.3%
615	3	2.3%
820	2	1.5%
572	2	1.5%
689	2	1.5%
655	1	0.8%
Other values (10)	10	7.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	66	50.4%
11	3	2.3%
20	1	0.8%
79	1	0.8%
128	1	0.8%
276	20	15.3%
298	1	0.8%
307	7	5.3%
318	1	0.8%
418	1	0.8%

Value	Count	Frequency (%)
855	1	0.8%
820	2	1.5%
689	2	1.5%
670	1	0.8%
655	1	0.8%
615	3	2.3%
572	2	1.5%
547	15	11.5%
464	1	0.8%
444	1	0.8%

fec_con_
Date

HIGH CORRELATION

Distinct	89
Distinct (%)	67.9%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

Minimum	2021-01-06 00:00:00
Maximum	2021-06-06 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

pac_hos_
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	121
2	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	2
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	121	92.4%
2	10	7.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	121	92.4%
2	10	7.6%

Most occurring characters

Value	Count	Frequency (%)
1	121	92.4%
2	10	7.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	121	92.4%
2	10	7.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	121	92.4%
2	10	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	121	92.4%
2	10	7.6%

fec_hos_
Unsupported

REJECTED
UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

fecha_nto_
Date

Distinct	127
Distinct (%)	96.9%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

Minimum	1973-12-12 00:00:00
Maximum	2006-04-06 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

fec_aju_
Date

HIGH CORRELATION

Distinct	67
Distinct (%)	51.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

Minimum	2021-01-09 00:00:00
Maximum	2021-06-21 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

nit_upgd
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	3.3%
Missing	9
Missing (%)	6.9%
Memory size	1.1 KiB

9000060374.0	43
8902087588.0	40
8902096989.0	27
8000842062.0	12

Length

Max length	12
Median length	12
Mean length	12
Min length	12

Characters and Unicode

Total characters	1464
Distinct characters	10
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	9000060374.0
2nd row	8000842062.0
3rd row	8000842062.0
4th row	9000060374.0
5th row	9000060374.0

Common Values

Value	Count	Frequency (%)
9000060374.0	43	32.8%
8902087588.0	40	30.5%
8902096989.0	27	20.6%
8000842062.0	12	9.2%
(Missing)	9	6.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
9000060374.0	43	35.2%
8902087588.0	40	32.8%
8902096989.0	27	22.1%
8000842062.0	12	9.8%

Most occurring characters

Value	Count	Frequency (%)
0	519	35.5%
8	238	16.3%
9	191	13.0%
.	122	8.3%
2	91	6.2%
7	83	5.7%
6	82	5.6%
4	55	3.8%
3	43	2.9%
5	40	2.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1342	91.7%
Other Punctuation	122	8.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	519	38.7%
8	238	17.7%
9	191	14.2%
2	91	6.8%
7	83	6.2%
6	82	6.1%
4	55	4.1%
3	43	3.2%
5	40	3.0%

Other Punctuation

Value	Count	Frequency (%)
.	122	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1464	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	519	35.5%
8	238	16.3%
9	191	13.0%
.	122	8.3%
2	91	6.2%
7	83	5.7%
6	82	5.6%
4	55	3.8%
3	43	2.9%
5	40	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1464	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	519	35.5%
8	238	16.3%
9	191	13.0%
.	122	8.3%
2	91	6.2%
7	83	5.7%
6	82	5.6%
4	55	3.8%
3	43	2.9%
5	40	2.7%

version
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

SIVIGILA - 2018 -18.2.0$0$1.0	90
SIVIGILA - 2018 - 18.2.0	24
SIVIGILA - 2018 -18.1.10$0$0.2	12
SIVIGILA - 2018 - 18.1.10	3
SIVIGILA - 2018 -18.3.0$0$0.1	2

Length

Max length	30
Median length	29
Mean length	28.08396947
Min length	24

Characters and Unicode

Total characters	3679
Distinct characters	15
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	SIVIGILA - 2018 -18.2.0$0$1.0
2nd row	SIVIGILA - 2018 - 18.2.0
3rd row	SIVIGILA - 2018 - 18.2.0
4th row	SIVIGILA - 2018 -18.1.10$0$0.2
5th row	SIVIGILA - 2018 -18.1.10$0$0.2

Common Values

Value	Count	Frequency (%)
SIVIGILA - 2018 -18.2.0$0$1.0	90	68.7%
SIVIGILA - 2018 - 18.2.0	24	18.3%
SIVIGILA - 2018 -18.1.10$0$0.2	12	9.2%
SIVIGILA - 2018 - 18.1.10	3	2.3%
SIVIGILA - 2018 -18.3.0$0$0.1	2	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	158	28.7%
2018	131	23.8%
sivigila	131	23.8%
18.2.0$0$1.0	90	16.3%
18.2.0	24	4.4%
18.1.10$0$0.2	12	2.2%
18.1.10	3	0.5%
18.3.0$0$0.1	2	0.4%

Most occurring characters

Value	Count	Frequency (%)
0	470	12.8%
	420	11.4%
I	393	10.7%
1	384	10.4%
.	366	9.9%
-	262	7.1%
8	262	7.1%
2	257	7.0%
$	208	5.7%
S	131	3.6%
Other values (5)	526	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1375	37.4%
Uppercase Letter	1048	28.5%
Space Separator	420	11.4%
Other Punctuation	366	9.9%
Dash Punctuation	262	7.1%
Currency Symbol	208	5.7%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	393	37.5%
S	131	12.5%
V	131	12.5%
G	131	12.5%
L	131	12.5%
A	131	12.5%

Decimal Number

Value	Count	Frequency (%)
0	470	34.2%
1	384	27.9%
8	262	19.1%
2	257	18.7%
3	2	0.1%

Space Separator

Value	Count	Frequency (%)
	420	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	262	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	366	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	208	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2631	71.5%
Latin	1048	28.5%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	470	17.9%
	420	16.0%
1	384	14.6%
.	366	13.9%
-	262	10.0%
8	262	10.0%
2	257	9.8%
$	208	7.9%
3	2	0.1%

Latin

Value	Count	Frequency (%)
I	393	37.5%
S	131	12.5%
V	131	12.5%
G	131	12.5%
L	131	12.5%
A	131	12.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3679	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	470	12.8%
	420	11.4%
I	393	10.7%
1	384	10.4%
.	366	9.9%
-	262	7.1%
8	262	7.1%
2	257	7.0%
$	208	5.7%
S	131	3.6%
Other values (5)	526	14.3%

tip_doc_rn
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

MS	86
CN	44
PE	1

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	262
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.8%

Sample

1st row	MS
2nd row	MS
3rd row	MS
4th row	MS
5th row	MS

Common Values

Value	Count	Frequency (%)
MS	86	65.6%
CN	44	33.6%
PE	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
ms	86	65.6%
cn	44	33.6%
pe	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
M	86	32.8%
S	86	32.8%
C	44	16.8%
N	44	16.8%
P	1	0.4%
E	1	0.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	262	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
M	86	32.8%
S	86	32.8%
C	44	16.8%
N	44	16.8%
P	1	0.4%
E	1	0.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	262	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
M	86	32.8%
S	86	32.8%
C	44	16.8%
N	44	16.8%
P	1	0.4%
E	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	262	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
M	86	32.8%
S	86	32.8%
C	44	16.8%
N	44	16.8%
P	1	0.4%
E	1	0.4%

no_ide_rn
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	131
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

164452072	1
164484846	1
163793919	1
1005136505	1
1005307711-1	1
Other values (126)	126

Length

Max length	15
Median length	10
Mean length	10.48091603
Min length	8

Characters and Unicode

Total characters	1373
Distinct characters	15
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	131 ?
Unique (%)	100.0%

Sample

1st row	37372773-4
2nd row	1098713904-1
3rd row	1099940520-2
4th row	1000251004-2
5th row	1000251004-1

Common Values

Value	Count	Frequency (%)
164452072	1	0.8%
164484846	1	0.8%
163793919	1	0.8%
1005136505	1	0.8%
1005307711-1	1	0.8%
164467640	1	0.8%
164484077	1	0.8%
1101200798-1	1	0.8%
1098409345-1	1	0.8%
10986856621	1	0.8%
Other values (121)	121	92.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ven27738184	1	0.8%
1095832837-1	1	0.8%
164487358	1	0.8%
163793919	1	0.8%
1005136505	1	0.8%
1005307711-1	1	0.8%
164467640	1	0.8%
164484077	1	0.8%
1101200798-1	1	0.8%
1098409345-1	1	0.8%
Other values (121)	121	92.4%

Most occurring characters

Value	Count	Frequency (%)
1	259	18.9%
4	154	11.2%
6	153	11.1%
0	138	10.1%
8	111	8.1%
3	102	7.4%
9	102	7.4%
7	91	6.6%
5	86	6.3%
2	83	6.0%
Other values (5)	94	6.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1279	93.2%
Dash Punctuation	60	4.4%
Uppercase Letter	33	2.4%
Space Separator	1	0.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	259	20.3%
4	154	12.0%
6	153	12.0%
0	138	10.8%
8	111	8.7%
3	102	8.0%
9	102	8.0%
7	91	7.1%
5	86	6.7%
2	83	6.5%

Uppercase Letter

Value	Count	Frequency (%)
V	11	33.3%
E	11	33.3%
N	11	33.3%

Dash Punctuation

Value	Count	Frequency (%)
-	60	100.0%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1340	97.6%
Latin	33	2.4%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	259	19.3%
4	154	11.5%
6	153	11.4%
0	138	10.3%
8	111	8.3%
3	102	7.6%
9	102	7.6%
7	91	6.8%
5	86	6.4%
2	83	6.2%
Other values (2)	61	4.6%

Latin

Value	Count	Frequency (%)
V	11	33.3%
E	11	33.3%
N	11	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1373	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	259	18.9%
4	154	11.2%
6	153	11.1%
0	138	10.1%
8	111	8.1%
3	102	7.4%
9	102	7.4%
7	91	6.6%
5	86	6.3%
2	83	6.0%
Other values (5)	94	6.8%

fecha_nac
Date

HIGH CORRELATION

Distinct	90
Distinct (%)	68.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

Minimum	2021-01-06 00:00:00
Maximum	2021-06-06 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

edad_rn
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	21
Distinct (%)	16.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.557251908

Minimum	0
Maximum	45
Zeros	5
Zeros (%)	3.8%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	4
Q3	7
95-th percentile	16
Maximum	45
Range	45
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	6.614855432
Coefficient of variation (CV)	1.190310524
Kurtosis	15.04142209
Mean	5.557251908
Median Absolute Deviation (MAD)	2
Skewness	3.411140944
Sum	728
Variance	43.75631239
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
1	23	17.6%
2	18	13.7%
3	18	13.7%
5	12	9.2%
4	11	8.4%
7	10	7.6%
6	8	6.1%
0	5	3.8%
11	5	3.8%
8	4	3.1%
Other values (11)	17	13.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5	3.8%
1	23	17.6%
2	18	13.7%
3	18	13.7%
4	11	8.4%
5	12	9.2%
6	8	6.1%
7	10	7.6%
8	4	3.1%
9	2	1.5%

Value	Count	Frequency (%)
45	1	0.8%
38	1	0.8%
33	1	0.8%
24	1	0.8%
17	1	0.8%
16	3	2.3%
15	1	0.8%
14	1	0.8%
12	2	1.5%
11	5	3.8%

sexo
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

F	79
M	52

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	F
2nd row	M
3rd row	F
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
F	79	60.3%
M	52	39.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	79	60.3%
m	52	39.7%

Most occurring characters

Value	Count	Frequency (%)
F	79	60.3%
M	52	39.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	131	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
F	79	60.3%
M	52	39.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	131	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	79	60.3%
M	52	39.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	79	60.3%
M	52	39.7%

peso_nacer
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	71
Distinct (%)	54.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2302.603053

Minimum	1655
Maximum	2490
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1655
5-th percentile	1997.5
Q1	2220
median	2335
Q3	2440
95-th percentile	2480
Maximum	2490
Range	835
Interquartile range (IQR)	220

Descriptive statistics

Standard deviation	164.8139128
Coefficient of variation (CV)	0.07157721454
Kurtosis	2.40181567
Mean	2302.603053
Median Absolute Deviation (MAD)	110
Skewness	-1.387742201
Sum	301641
Variance	27163.62584
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2375	6	4.6%
2100	6	4.6%
2270	5	3.8%
2470	5	3.8%
2465	4	3.1%
2480	4	3.1%
2475	4	3.1%
2450	3	2.3%
2485	3	2.3%
2255	3	2.3%
Other values (61)	88	67.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1655	1	0.8%
1755	1	0.8%
1800	1	0.8%
1810	1	0.8%
1910	1	0.8%
1930	1	0.8%
1965	1	0.8%
2030	1	0.8%
2040	1	0.8%
2080	1	0.8%

Value	Count	Frequency (%)
2490	3	2.3%
2485	3	2.3%
2480	4	3.1%
2475	4	3.1%
2470	5	3.8%
2465	4	3.1%
2460	3	2.3%
2455	1	0.8%
2450	3	2.3%
2445	1	0.8%

talla_nace
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	14
Distinct (%)	10.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	47.16030534

Minimum	42
Maximum	52
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	42
5-th percentile	44
Q1	46
median	47
Q3	48
95-th percentile	50
Maximum	52
Range	10
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.858729069
Coefficient of variation (CV)	0.03941299904
Kurtosis	0.2035621377
Mean	47.16030534
Median Absolute Deviation (MAD)	1
Skewness	-0.009774317438
Sum	6178
Variance	3.454873752
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
48	32	24.4%
47	29	22.1%
45	17	13.0%
46	17	13.0%
49	10	7.6%
50	7	5.3%
44	4	3.1%
43	3	2.3%
51	3	2.3%
49.5	3	2.3%
Other values (4)	6	4.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
42	1	0.8%
43	3	2.3%
44	4	3.1%
45	17	13.0%
45.5	2	1.5%
46	17	13.0%
47	29	22.1%
48	32	24.4%
48.5	1	0.8%
49	10	7.6%

Value	Count	Frequency (%)
52	2	1.5%
51	3	2.3%
50	7	5.3%
49.5	3	2.3%
49	10	7.6%
48.5	1	0.8%
48	32	24.4%
47	29	22.1%
46	17	13.0%
45.5	2	1.5%

sem_gest
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

37	98
38	20
39	11
40	2

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	262
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	37
2nd row	37
3rd row	39
4th row	37
5th row	37

Common Values

Value	Count	Frequency (%)
37	98	74.8%
38	20	15.3%
39	11	8.4%
40	2	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
37	98	74.8%
38	20	15.3%
39	11	8.4%
40	2	1.5%

Most occurring characters

Value	Count	Frequency (%)
3	129	49.2%
7	98	37.4%
8	20	7.6%
9	11	4.2%
4	2	0.8%
0	2	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	262	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	129	49.2%
7	98	37.4%
8	20	7.6%
9	11	4.2%
4	2	0.8%
0	2	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	262	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	129	49.2%
7	98	37.4%
8	20	7.6%
9	11	4.2%
4	2	0.8%
0	2	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	262	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	129	49.2%
7	98	37.4%
8	20	7.6%
9	11	4.2%
4	2	0.8%
0	2	0.8%

mult_embar
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	124
2	7

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
1	124	94.7%
2	7	5.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	124	94.7%
2	7	5.3%

Most occurring characters

Value	Count	Frequency (%)
1	124	94.7%
2	7	5.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	124	94.7%
2	7	5.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	124	94.7%
2	7	5.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	124	94.7%
2	7	5.3%

num_em_pre
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	4.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.007633588

Minimum	0
Maximum	5
Zeros	62
Zeros (%)	47.3%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	2
95-th percentile	3
Maximum	5
Range	5
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.205731079
Coefficient of variation (CV)	1.196596752
Kurtosis	0.274921461
Mean	1.007633588
Median Absolute Deviation (MAD)	1
Skewness	1.054711092
Sum	132
Variance	1.453787434
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	62	47.3%
1	31	23.7%
2	19	14.5%
3	14	10.7%
4	4	3.1%
5	1	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	62	47.3%
1	31	23.7%
2	19	14.5%
3	14	10.7%
4	4	3.1%
5	1	0.8%

Value	Count	Frequency (%)
5	1	0.8%
4	4	3.1%
3	14	10.7%
2	19	14.5%
1	31	23.7%
0	62	47.3%

num_hi_viv
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	73
2	38
3	15
4	4
5	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	131
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.8%

Sample

1st row	4
2nd row	1
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
1	73	55.7%
2	38	29.0%
3	15	11.5%
4	4	3.1%
5	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	73	55.7%
2	38	29.0%
3	15	11.5%
4	4	3.1%
5	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
1	73	55.7%
2	38	29.0%
3	15	11.5%
4	4	3.1%
5	1	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	131	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	73	55.7%
2	38	29.0%
3	15	11.5%
4	4	3.1%
5	1	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	131	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	73	55.7%
2	38	29.0%
3	15	11.5%
4	4	3.1%
5	1	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	131	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	73	55.7%
2	38	29.0%
3	15	11.5%
4	4	3.1%
5	1	0.8%

niv_edu_ma
Categorical

HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	3.1%
Missing	2
Missing (%)	1.5%
Memory size	1.1 KiB

2.0	64
3.0	43
1.0	21
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	387
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.8%

Sample

1st row	1.0
2nd row	1.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	64	48.9%
3.0	43	32.8%
1.0	21	16.0%
4.0	1	0.8%
(Missing)	2	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	64	49.6%
3.0	43	33.3%
1.0	21	16.3%
4.0	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
.	129	33.3%
0	129	33.3%
2	64	16.5%
3	43	11.1%
1	21	5.4%
4	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	258	66.7%
Other Punctuation	129	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	129	50.0%
2	64	24.8%
3	43	16.7%
1	21	8.1%
4	1	0.4%

Other Punctuation

Value	Count	Frequency (%)
.	129	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	387	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	129	33.3%
0	129	33.3%
2	64	16.5%
3	43	11.1%
1	21	5.4%
4	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	387	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	129	33.3%
0	129	33.3%
2	64	16.5%
3	43	11.1%
1	21	5.4%
4	1	0.3%

nom_upgd
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	4.1%
Missing	9
Missing (%)	6.9%
Memory size	1.1 KiB

HOSPITAL UNIVERSITARIO DE SANTANDER	43
CLINICA MATERNO INFANTIL SAN LUIS SA	40
CLINICA CHICAMOCHA SA	27
HOSPITAL LOCAL DEL NORTE	10
UIMIST	2

Length

Max length	36
Median length	35
Mean length	30.85245902
Min length	6

Characters and Unicode

Total characters	3764
Distinct characters	18
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	HOSPITAL UNIVERSITARIO DE SANTANDER
2nd row	HOSPITAL LOCAL DEL NORTE
3rd row	HOSPITAL LOCAL DEL NORTE
4th row	HOSPITAL UNIVERSITARIO DE SANTANDER
5th row	HOSPITAL UNIVERSITARIO DE SANTANDER

Common Values

Value	Count	Frequency (%)
HOSPITAL UNIVERSITARIO DE SANTANDER	43	32.8%
CLINICA MATERNO INFANTIL SAN LUIS SA	40	30.5%
CLINICA CHICAMOCHA SA	27	20.6%
HOSPITAL LOCAL DEL NORTE	10	7.6%
UIMIST	2	1.5%
(Missing)	9	6.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
sa	67	12.5%
clinica	67	12.5%
hospital	53	9.9%
santander	43	8.0%
universitario	43	8.0%
de	43	8.0%
san	40	7.5%
materno	40	7.5%
infantil	40	7.5%
luis	40	7.5%
Other values (5)	59	11.0%

Most occurring characters

Value	Count	Frequency (%)
A	500	13.3%
I	467	12.4%
	413	11.0%
N	366	9.7%
S	288	7.7%
T	231	6.1%
L	230	6.1%
C	225	6.0%
E	189	5.0%
O	183	4.9%
Other values (8)	672	17.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	3351	89.0%
Space Separator	413	11.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	500	14.9%
I	467	13.9%
N	366	10.9%
S	288	8.6%
T	231	6.9%
L	230	6.9%
C	225	6.7%
E	189	5.6%
O	183	5.5%
R	179	5.3%
Other values (7)	493	14.7%

Space Separator

Value	Count	Frequency (%)
	413	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3351	89.0%
Common	413	11.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	500	14.9%
I	467	13.9%
N	366	10.9%
S	288	8.6%
T	231	6.9%
L	230	6.9%
C	225	6.7%
E	189	5.6%
O	183	5.5%
R	179	5.3%
Other values (7)	493	14.7%

Common

Value	Count	Frequency (%)
	413	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3764	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	500	13.3%
I	467	12.4%
	413	11.0%
N	366	9.7%
S	288	7.7%
T	231	6.1%
L	230	6.1%
C	225	6.0%
E	189	5.0%
O	183	4.9%
Other values (8)	672	17.9%

ndep_proce
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

SANTANDER	125
CESAR	3
BOLIVAR	2
NORTE SANTANDER	1

Length

Max length	15
Median length	9
Mean length	8.923664122
Min length	5

Characters and Unicode

Total characters	1169
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.8%

Sample

1st row	SANTANDER
2nd row	SANTANDER
3rd row	SANTANDER
4th row	SANTANDER
5th row	SANTANDER

Common Values

Value	Count	Frequency (%)
SANTANDER	125	95.4%
CESAR	3	2.3%
BOLIVAR	2	1.5%
NORTE SANTANDER	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
santander	126	95.5%
cesar	3	2.3%
bolivar	2	1.5%
norte	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
A	257	22.0%
N	253	21.6%
R	132	11.3%
E	130	11.1%
S	129	11.0%
T	127	10.9%
D	126	10.8%
O	3	0.3%
C	3	0.3%
B	2	0.2%
Other values (4)	7	0.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1168	99.9%
Space Separator	1	0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	257	22.0%
N	253	21.7%
R	132	11.3%
E	130	11.1%
S	129	11.0%
T	127	10.9%
D	126	10.8%
O	3	0.3%
C	3	0.3%
B	2	0.2%
Other values (3)	6	0.5%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1168	99.9%
Common	1	0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	257	22.0%
N	253	21.7%
R	132	11.3%
E	130	11.1%
S	129	11.0%
T	127	10.9%
D	126	10.8%
O	3	0.3%
C	3	0.3%
B	2	0.2%
Other values (3)	6	0.5%

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1169	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	257	22.0%
N	253	21.6%
R	132	11.3%
E	130	11.1%
S	129	11.0%
T	127	10.9%
D	126	10.8%
O	3	0.3%
C	3	0.3%
B	2	0.2%
Other values (4)	7	0.6%

nmun_proce
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	21
Distinct (%)	16.0%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

BUCARAMANGA	60
FLORIDABLANCA	22
PIEDECUESTA	15
GIRON	7
TONA	4
Other values (16)	23

Length

Max length	22
Median length	11
Mean length	10.73282443
Min length	4

Characters and Unicode

Total characters	1406
Distinct characters	22
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11 ?
Unique (%)	8.4%

Sample

1st row	SAN VICENTE DE CHUCURI
2nd row	CIMITARRA
3rd row	TONA
4th row	PUENTE NACIONAL
5th row	PUENTE NACIONAL

Common Values

Value	Count	Frequency (%)
BUCARAMANGA	60	45.8%
FLORIDABLANCA	22	16.8%
PIEDECUESTA	15	11.5%
GIRON	7	5.3%
TONA	4	3.1%
RIONEGRO	3	2.3%
AGUACHICA	3	2.3%
PUENTE NACIONAL	2	1.5%
SAN PABLO	2	1.5%
SAN VICENTE DE CHUCURI	2	1.5%
Other values (11)	11	8.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
bucaramanga	60	40.8%
floridablanca	22	15.0%
piedecuesta	15	10.2%
giron	7	4.8%
san	5	3.4%
tona	4	2.7%
de	4	2.7%
rionegro	3	2.0%
aguachica	3	2.0%
chucuri	2	1.4%
Other values (18)	22	15.0%

Most occurring characters

Value	Count	Frequency (%)
A	367	26.1%
C	116	8.3%
N	113	8.0%
R	104	7.4%
B	88	6.3%
U	85	6.0%
G	76	5.4%
E	64	4.6%
M	64	4.6%
I	62	4.4%
Other values (12)	267	19.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1390	98.9%
Space Separator	16	1.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	367	26.4%
C	116	8.3%
N	113	8.1%
R	104	7.5%
B	88	6.3%
U	85	6.1%
G	76	5.5%
E	64	4.6%
M	64	4.6%
I	62	4.5%
Other values (11)	251	18.1%

Space Separator

Value	Count	Frequency (%)
	16	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1390	98.9%
Common	16	1.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	367	26.4%
C	116	8.3%
N	113	8.1%
R	104	7.5%
B	88	6.3%
U	85	6.1%
G	76	5.5%
E	64	4.6%
M	64	4.6%
I	62	4.5%
Other values (11)	251	18.1%

Common

Value	Count	Frequency (%)
	16	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1406	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	367	26.1%
C	116	8.3%
N	113	8.0%
R	104	7.4%
B	88	6.3%
U	85	6.0%
G	76	5.4%
E	64	4.6%
M	64	4.6%
I	62	4.4%
Other values (12)	267	19.0%

ndep_resi
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

SANTANDER	126
CESAR	3
BOLIVAR	1
NORTE SANTANDER	1

Length

Max length	15
Median length	9
Mean length	8.938931298
Min length	5

Characters and Unicode

Total characters	1171
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.5%

Sample

1st row	SANTANDER
2nd row	SANTANDER
3rd row	SANTANDER
4th row	SANTANDER
5th row	SANTANDER

Common Values

Value	Count	Frequency (%)
SANTANDER	126	96.2%
CESAR	3	2.3%
BOLIVAR	1	0.8%
NORTE SANTANDER	1	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
santander	127	96.2%
cesar	3	2.3%
norte	1	0.8%
bolivar	1	0.8%

Most occurring characters

Value	Count	Frequency (%)
A	258	22.0%
N	255	21.8%
R	132	11.3%
E	131	11.2%
S	130	11.1%
T	128	10.9%
D	127	10.8%
C	3	0.3%
O	2	0.2%
B	1	0.1%
Other values (4)	4	0.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1170	99.9%
Space Separator	1	0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	258	22.1%
N	255	21.8%
R	132	11.3%
E	131	11.2%
S	130	11.1%
T	128	10.9%
D	127	10.9%
C	3	0.3%
O	2	0.2%
B	1	0.1%
Other values (3)	3	0.3%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1170	99.9%
Common	1	0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	258	22.1%
N	255	21.8%
R	132	11.3%
E	131	11.2%
S	130	11.1%
T	128	10.9%
D	127	10.9%
C	3	0.3%
O	2	0.2%
B	1	0.1%
Other values (3)	3	0.3%

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1171	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	258	22.0%
N	255	21.8%
R	132	11.3%
E	131	11.2%
S	130	11.1%
T	128	10.9%
D	127	10.8%
C	3	0.3%
O	2	0.2%
B	1	0.1%
Other values (4)	4	0.3%

nmun_resi
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	20
Distinct (%)	15.3%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

BUCARAMANGA	66
FLORIDABLANCA	20
PIEDECUESTA	15
GIRON	7
RIONEGRO	3
Other values (15)	20

Length

Max length	22
Median length	11
Mean length	10.83969466
Min length	4

Characters and Unicode

Total characters	1420
Distinct characters	22
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11 ?
Unique (%)	8.4%

Sample

1st row	SAN VICENTE DE CHUCURI
2nd row	BUCARAMANGA
3rd row	BUCARAMANGA
4th row	PUENTE NACIONAL
5th row	PUENTE NACIONAL

Common Values

Value	Count	Frequency (%)
BUCARAMANGA	66	50.4%
FLORIDABLANCA	20	15.3%
PIEDECUESTA	15	11.5%
GIRON	7	5.3%
RIONEGRO	3	2.3%
AGUACHICA	3	2.3%
SAN VICENTE DE CHUCURI	2	1.5%
PUENTE NACIONAL	2	1.5%
TONA	2	1.5%
VALLE DE SAN JOSE	1	0.8%
Other values (10)	10	7.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
bucaramanga	66	45.2%
floridablanca	20	13.7%
piedecuesta	15	10.3%
giron	7	4.8%
san	4	2.7%
de	4	2.7%
rionegro	3	2.1%
aguachica	3	2.1%
puente	2	1.4%
chucuri	2	1.4%
Other values (17)	20	13.7%

Most occurring characters

Value	Count	Frequency (%)
A	379	26.7%
C	119	8.4%
N	114	8.0%
R	106	7.5%
U	91	6.4%
B	91	6.4%
G	82	5.8%
M	69	4.9%
E	64	4.5%
I	58	4.1%
Other values (12)	247	17.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1405	98.9%
Space Separator	15	1.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	379	27.0%
C	119	8.5%
N	114	8.1%
R	106	7.5%
U	91	6.5%
B	91	6.5%
G	82	5.8%
M	69	4.9%
E	64	4.6%
I	58	4.1%
Other values (11)	232	16.5%

Space Separator

Value	Count	Frequency (%)
	15	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1405	98.9%
Common	15	1.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	379	27.0%
C	119	8.5%
N	114	8.1%
R	106	7.5%
U	91	6.5%
B	91	6.5%
G	82	5.8%
M	69	4.9%
E	64	4.6%
I	58	4.1%
Other values (11)	232	16.5%

Common

Value	Count	Frequency (%)
	15	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1420	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	379	26.7%
C	119	8.4%
N	114	8.0%
R	106	7.5%
U	91	6.4%
B	91	6.4%
G	82	5.8%
M	69	4.9%
E	64	4.5%
I	58	4.1%
Other values (12)	247	17.4%

nreg
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	131
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	66.12977099

Minimum	1
Maximum	134
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1
5-th percentile	7.5
Q1	33.5
median	66
Q3	98.5
95-th percentile	125.5
Maximum	134
Range	133
Interquartile range (IQR)	65

Descriptive statistics

Standard deviation	38.17034631
Coefficient of variation (CV)	0.577203667
Kurtosis	-1.18117262
Mean	66.12977099
Median Absolute Deviation (MAD)	33
Skewness	0.01656812293
Sum	8663
Variance	1456.975338
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	0.8%
99	1	0.8%
97	1	0.8%
96	1	0.8%
95	1	0.8%
94	1	0.8%
93	1	0.8%
92	1	0.8%
91	1	0.8%
90	1	0.8%
Other values (121)	121	92.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.8%
2	1	0.8%
3	1	0.8%
4	1	0.8%
5	1	0.8%
6	1	0.8%
7	1	0.8%
8	1	0.8%
9	1	0.8%
10	1	0.8%

Value	Count	Frequency (%)
134	1	0.8%
133	1	0.8%
130	1	0.8%
129	1	0.8%
128	1	0.8%
127	1	0.8%
126	1	0.8%
125	1	0.8%
124	1	0.8%
123	1	0.8%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	fec_not	semana	cod_pre	tip_ide_	num_ide_	edad_	nacionali_	nombre_nacionalidad	cod_dpto_o	cod_mun_o	area_	ocupacion_	tip_ss_	cod_ase_	estrato_	gp_migrant	gp_gestan	sem_ges_	gp_otros	cod_dpto_r	cod_mun_r	fec_con_	pac_hos_	fec_hos_	fecha_nto_	fec_aju_	nit_upgd	version	tip_doc_rn	no_ide_rn	fecha_nac	edad_rn	sexo	peso_nacer	talla_nace	sem_gest	mult_embar	num_em_pre	num_hi_viv	niv_edu_ma	nom_upgd	ndep_proce	nmun_proce	ndep_resi	nmun_resi	nreg
0	2021-05-19	19	6800100792	CC	37372773	36	170	COLOMBIA	68	689	3	9996	S	EPSS41	NaN	2	2	NaN	1	68	689	2021-05-11	1	2021-05-11 00:00:00	1985-02-19	2021-05-19	9.000060e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	37372773-4	2021-05-11	11	F	2100	45.0	37	1	3	4	1.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	SAN VICENTE DE CHUCURI	SANTANDER	SAN VICENTE DE CHUCURI	118
1	2021-01-25	4	6800100701	CC	1098713904	30	170	COLOMBIA	68	190	2	9996	S	EPSS41	1.0	2	2	NaN	1	68	1	2021-01-25	2	- -	1990-10-24	2021-02-26	8.000842e+09	SIVIGILA - 2018 - 18.2.0	MS	1098713904-1	2021-01-25	0	M	2320	44.0	37	1	1	1	1.0	HOSPITAL LOCAL DEL NORTE	SANTANDER	CIMITARRA	SANTANDER	BUCARAMANGA	38
2	2021-03-04	8	6800100701	CC	1099940520	22	170	COLOMBIA	68	820	3	9996	S	ESS133	1.0	2	2	NaN	1	68	1	2021-02-25	1	2021-02-25 00:00:00	1998-04-26	2021-04-16	8.000842e+09	SIVIGILA - 2018 - 18.2.0	MS	1099940520-2	2021-02-25	7	F	2320	47.0	39	1	1	2	2.0	HOSPITAL LOCAL DEL NORTE	SANTANDER	TONA	SANTANDER	BUCARAMANGA	85
3	2021-01-11	1	6800100792	CC	1000251004	20	170	COLOMBIA	68	572	3	9996	S	ESS024	NaN	2	2	NaN	1	68	572	2021-01-07	1	2021-01-07 00:00:00	2000-08-19	2021-01-11	9.000060e+09	SIVIGILA - 2018 -18.1.10$0$0.2	MS	1000251004-2	2021-01-07	4	F	2280	49.5	37	1	1	2	2.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	PUENTE NACIONAL	SANTANDER	PUENTE NACIONAL	1
4	2021-01-11	1	6800100792	CC	1000251004-1	20	170	COLOMBIA	68	572	3	9996	S	ESS024	NaN	2	2	NaN	1	68	572	2021-01-07	1	2021-01-07 00:00:00	2000-08-19	2021-01-11	9.000060e+09	SIVIGILA - 2018 -18.1.10$0$0.2	MS	1000251004-1	2021-01-07	4	F	2270	45.5	37	2	1	2	2.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	PUENTE NACIONAL	SANTANDER	PUENTE NACIONAL	2
5	2021-01-18	1	6800100792	CC	1005234909	24	170	COLOMBIA	68	307	1	9996	S	EPSS37	2.0	2	1	38.0	1	68	307	2021-01-08	1	2021-01-08 00:00:00	1996-04-13	2021-01-18	9.000060e+09	SIVIGILA - 2018 - 18.1.10	MS	1005234909	2021-01-08	10	M	2345	48.0	38	1	0	1	2.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	GIRON	SANTANDER	GIRON	4
6	2021-01-08	1	6800100431	CC	1193149502	20	170	COLOMBIA	68	547	1	9999	S	EPSS02	NaN	2	2	NaN	1	68	547	2021-01-08	2	- -	2000-07-31	2021-01-24	8.902088e+09	SIVIGILA - 2018 -18.1.10$0$0.2	MS	1193149502-1	2021-01-08	16	M	2490	47.0	37	1	0	1	2.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	PIEDECUESTA	SANTANDER	PIEDECUESTA	11
7	2021-01-06	1	6827600717	MS	VEN31583030	17	862	VENEZUELA	68	1	1	9996	N	NaN	1.0	1	2	NaN	2	68	1	2021-01-06	1	2021-01-06 00:00:00	2003-07-17	2021-01-09	NaN	SIVIGILA - 2018 -18.1.10$0$0.2	MS	3158303002	2021-01-06	3	M	2460	46.0	38	1	1	2	2.0	NaN	SANTANDER	BUCARAMANGA	SANTANDER	BUCARAMANGA	16
8	2021-03-12	10	6800100792	CC	1005136505	24	170	COLOMBIA	68	1	1	9996	S	ESS024	NaN	2	1	37.0	1	68	1	2021-03-10	1	2021-03-11 00:00:00	1996-09-23	2021-03-12	9.000060e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1005136505	2021-03-11	1	M	2185	47.0	37	1	0	2	2.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	BUCARAMANGA	SANTANDER	BUCARAMANGA	57
9	2021-03-09	10	6800100431	CC	1005484353	28	170	COLOMBIA	68	276	1	9999	C	EPS005	NaN	2	2	NaN	1	68	276	2021-03-08	1	2021-03-09 00:00:00	1992-10-06	2021-03-14	8.902088e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1005484353-1	2021-03-09	5	F	2270	49.0	39	1	1	2	2.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	FLORIDABLANCA	SANTANDER	FLORIDABLANCA	55

Last rows

	fec_not	semana	cod_pre	tip_ide_	num_ide_	edad_	nacionali_	nombre_nacionalidad	cod_dpto_o	cod_mun_o	area_	ocupacion_	tip_ss_	cod_ase_	estrato_	gp_migrant	gp_gestan	sem_ges_	gp_otros	cod_dpto_r	cod_mun_r	fec_con_	pac_hos_	fec_hos_	fecha_nto_	fec_aju_	nit_upgd	version	tip_doc_rn	no_ide_rn	fecha_nac	edad_rn	sexo	peso_nacer	talla_nace	sem_gest	mult_embar	num_em_pre	num_hi_viv	niv_edu_ma	nom_upgd	ndep_proce	nmun_proce	ndep_resi	nmun_resi	nreg
121	2021-02-24	8	6800100431	CC	1005336655	23	170	COLOMBIA	68	1	1	9999	C	EPS002	NaN	2	2	NaN	1	68	1	2021-02-24	1	2021-02-24 00:00:00	1997-07-30	2021-02-27	8.902088e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1005336655-1	2021-02-24	3	M	2210	47.0	37	1	0	1	2.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	BUCARAMANGA	SANTANDER	BUCARAMANGA	46
122	2021-02-26	8	6800100431	CC	1007665960	20	170	COLOMBIA	68	1	1	9999	S	ESS133	NaN	2	2	NaN	1	68	1	2021-02-26	1	2021-02-26 00:00:00	2001-01-16	2021-02-27	8.902088e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1007665960-1	2021-02-26	1	M	2300	45.0	37	1	0	1	2.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	BUCARAMANGA	SANTANDER	BUCARAMANGA	45
123	2021-02-22	8	6800100431	CC	1095914784	32	170	COLOMBIA	68	547	1	9999	C	EPS010	NaN	2	2	NaN	1	68	547	2021-02-22	1	2021-02-22 00:00:00	1988-09-24	2021-02-27	8.902088e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1095914784-1	2021-02-22	5	F	2485	48.0	38	1	0	1	3.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	PIEDECUESTA	SANTANDER	PIEDECUESTA	44
124	2021-02-22	8	6800101157	CC	1102380004	24	170	COLOMBIA	68	547	1	9999	C	EPS046	3.0	2	1	37.0	2	68	547	2021-02-22	1	2021-02-22 00:00:00	1996-04-22	2021-02-23	8.902097e+09	SIVIGILA - 2018 -18.2.0$0$1.0	CN	164452873	2021-02-22	1	M	2380	48.0	37	1	0	1	3.0	CLINICA CHICAMOCHA SA	SANTANDER	PIEDECUESTA	SANTANDER	PIEDECUESTA	39
125	2021-02-22	8	6800100431	CC	1102717020	33	170	COLOMBIA	68	689	1	9999	S	ESS024	NaN	2	2	NaN	1	68	689	2021-02-22	1	2021-02-22 00:00:00	1987-10-11	2021-02-27	8.902088e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1102717020-1	2021-02-22	5	F	2280	47.0	37	1	1	2	1.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	SAN VICENTE DE CHUCURI	SANTANDER	SAN VICENTE DE CHUCURI	43
126	2021-02-25	8	6800100792	CE	VEN27355994	21	862	VENEZUELA	68	547	1	9996	N	NaN	1.0	1	2	NaN	1	68	547	2021-02-22	1	2021-02-22 00:00:00	1999-03-16	2021-02-25	9.000060e+09	SIVIGILA - 2018 - 18.2.0	MS	164452072	2021-02-22	3	M	2365	52.0	37	1	0	1	2.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	PIEDECUESTA	SANTANDER	PIEDECUESTA	41
127	2021-02-25	8	6800100792	TI	1098071245	15	170	COLOMBIA	68	444	3	9997	S	ESS062	1.0	2	2	NaN	1	68	444	2021-02-19	1	2021-02-19 00:00:00	2005-06-23	2021-02-25	9.000060e+09	SIVIGILA - 2018 - 18.2.0	MS	164452019	2021-02-22	3	F	2475	51.0	37	1	0	1	2.0	HOSPITAL UNIVERSITARIO DE SANTANDER	SANTANDER	MATANZA	SANTANDER	MATANZA	40
128	2021-03-05	9	6827601666	CC	1095956300	21	170	COLOMBIA	68	1	1	9996	S	EPSS37	3.0	2	2	NaN	1	68	1	2021-03-05	1	2021-03-05 00:00:00	1999-03-30	2021-03-07	NaN	SIVIGILA - 2018 -18.2.0$0$1.0	CN	164472939	2021-03-05	2	F	2215	46.0	37	1	2	1	2.0	NaN	SANTANDER	BUCARAMANGA	SANTANDER	BUCARAMANGA	50
129	2021-03-05	9	6800101157	CC	32791808	45	170	COLOMBIA	68	276	1	9999	C	EPS005	3.0	2	1	38.0	1	68	276	2021-03-03	1	2021-03-03 00:00:00	1975-03-25	2021-03-05	8.902097e+09	SIVIGILA - 2018 -18.2.0$0$1.0	CN	164453758	2021-03-03	2	F	2180	48.0	38	1	0	1	2.0	CLINICA CHICAMOCHA SA	SANTANDER	FLORIDABLANCA	SANTANDER	FLORIDABLANCA	48
130	2021-03-04	9	6800100431	TI	1102634593	17	170	COLOMBIA	68	820	1	9999	S	ESS133	NaN	2	2	NaN	1	68	1	2021-03-04	1	2021-03-04 00:00:00	2003-11-23	2021-03-06	8.902088e+09	SIVIGILA - 2018 -18.2.0$0$1.0	MS	1102634593-1	2021-03-04	2	F	2415	48.0	38	1	0	1	3.0	CLINICA MATERNO INFANTIL SAN LUIS SA	SANTANDER	TONA	SANTANDER	BUCARAMANGA	47

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Uppercase Letter

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks